CN113253219B - No-reference object self-calibration method, device, equipment and medium of millimeter wave radar - Google Patents
No-reference object self-calibration method, device, equipment and medium of millimeter wave radar Download PDFInfo
- Publication number
- CN113253219B CN113253219B CN202110754125.3A CN202110754125A CN113253219B CN 113253219 B CN113253219 B CN 113253219B CN 202110754125 A CN202110754125 A CN 202110754125A CN 113253219 B CN113253219 B CN 113253219B
- Authority
- CN
- China
- Prior art keywords
- angle
- radar
- straight line
- frame
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/40—Means for monitoring or calibrating
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The invention relates to the field of radar calibration, in particular to a method, a device, equipment and a medium for calibrating a millimeter wave radar without a reference object. The method comprises the following steps: the method comprises the steps that in the running process of a vehicle on an actual road, multi-frame data detected by a target radar are collected, and the position of a static reflection point is determined from each frame of data of the multi-frame data; identifying a straight line corresponding to each static reflecting point according to the position of each static reflecting point in each frame of data; calculating the included angle between each straight line and the normal line of the radar and the probability density of the included angle of each straight line; selecting an included angle of a straight line with the probability density meeting the requirement as a bias angle of the target radar; and self-calibrating the target radar according to the offset angle. The embodiment of the invention can realize the radar self-calibration without a reference object.
Description
Technical Field
The invention relates to the technical field of radar calibration, in particular to a method, a device, equipment and a medium for calibrating a millimeter wave radar without a reference object.
Background
The millimeter wave radar is a radar working in millimeter wave band detection, and has the characteristics of small volume, light weight and high spatial resolution. It is common for a target vehicle to have a millimeter wave radar mounted thereon to detect a forward field of view.
In the running process of a vehicle, if an accident occurs or the vehicle shakes and shakes for a long time, the millimeter wave radar may incline in the installation angle, and the radar needs to be calibrated again.
The calibration of the millimeter-wave radar by the target generally adopts a reference object with a fixed position, for example, a corner reflector and a guardrail, and the self-calibration is carried out through data detected by the radar. This method relies on an external reference and is not suitable for calibration when no external reference is present.
In view of the above, the present invention is particularly proposed.
Disclosure of Invention
The embodiment of the invention provides a method, a device, equipment and a storage medium for non-reference object self-calibration of a millimeter wave radar, and realizes the non-reference object radar self-calibration.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, the present invention provides a reference-free self-calibration method for a millimeter wave radar, including:
the method comprises the steps that in the running process of a vehicle on an actual road, multi-frame data detected by a target radar are collected, and the position of a static reflection point is determined from each frame of data of the multi-frame data;
identifying a straight line corresponding to each static reflecting point according to the position of each static reflecting point in each frame of data;
calculating the included angle between each straight line and the normal line of the radar and the probability density of the included angle of each straight line;
selecting an included angle of a straight line with the probability density meeting the requirement as a bias angle of the target radar;
and self-calibrating the target radar according to the offset angle.
In a second aspect, the present invention provides a reference-free self-calibration apparatus for millimeter-wave radar, including:
the acquisition module is used for acquiring multi-frame data detected by a target radar in the running process of a vehicle on an actual road and determining the position of a static reflection point from each frame of data of the multi-frame data;
the identification module is used for identifying straight lines corresponding to the static reflecting points according to the positions of the static reflecting points in each frame of data;
the calculation module is used for calculating the offset angle of each straight line relative to the normal line of the radar and the probability density of the offset angle of each straight line;
the selecting module is used for selecting the offset angle of the straight line with the probability density meeting the requirement as the offset angle of the target radar;
a calibration module for self-calibrating the target radar according to the offset angle
In a third aspect, the present invention provides an electronic device, comprising:
one or more processors;
a memory for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement any of the millimeter wave radar reference-free self-calibration methods.
In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor, implements a method for reference-free self-calibration of a millimeter wave radar as described in any one of the above.
Compared with the prior art, the invention has the beneficial effects that:
the method does not depend on any fixed reference object, the linear equation of the static object on the road profile is solved according to the distribution characteristics of the static object on the road profile, the probability density of the included angle is further calculated, and the bias angle of the radar is determined by adopting the idea of big data statistics. The calibration method is simpler and shorter in time consumption, and is suitable for almost all road scenes.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a reference-free self-calibration method for a millimeter-wave radar according to an embodiment of the present invention;
FIG. 2 is a diagram of a frame of probe data according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a radar normal provided by an embodiment of the present invention;
FIG. 4 is a schematic diagram of a probability density curve provided by an embodiment of the invention;
FIG. 5 is a schematic diagram of a display effect before calibration according to an embodiment of the present invention;
FIG. 6 is a diagram illustrating a calibrated display effect according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a reference-object-free self-calibration apparatus of a millimeter wave radar according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should also be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Fig. 1 is a flowchart of a method for self-calibration without a reference object for a millimeter wave radar according to an embodiment of the present invention, and is suitable for performing radar self-calibration without a reference object. The method can be carried out by a reference-free self-calibration device of a millimeter-wave radar, which is made up of hardware and/or software and is generally integrated in an electronic device. Referring to fig. 1, the method includes the operations of:
s110, collecting multi-frame data detected by a target radar in the running process of the vehicle on the actual road, and determining the position of a static reflection point from each frame of data of the multi-frame data.
The real vehicle in the embodiment runs on the actual road, the object on the road is not limited, the calibration is not carried out by the reference object at the fixed position, and the self-calibration is realized by utilizing all the collected static data on the road and combining the big data analysis.
On an actual road, there are many static objects distributed along the road contour, such as guard rails, continuous trees, etc., but the present invention does not limit the kinds, distribution, etc. of the static objects. When the vehicle runs, a millimeter wave radar (target radar) mounted on the vehicle collects detected multi-frame data in real time, wherein each frame of data comprises the position of each reflection point. Illustratively, the radar probes every 70ms, forming a frame of data. By analyzing the data of each frame in combination with the vehicle speed of the vehicle, it is possible to identify which static reflection points are and which dynamic reflection points are. In this embodiment, only the position of the static reflection point is extracted, and the category of the static reflection point is not distinguished.
And S120, identifying a straight line corresponding to each static reflecting point according to the position of each static reflecting point in each frame of data.
Fig. 2 is a schematic diagram of a frame of sounding data according to an embodiment of the present invention. The X-axis is along the transverse direction of the vehicle and the Y-axis is along the longitudinal direction of the vehicle, similar to the visual effect of looking down the road. Fig. 2 shows the reflection points as dots, the static reflection points as open dots, and the dynamic reflection points as filled dots. It can be known that as the vehicle travels, the number, position, etc. of the static reflection points dynamically change, reflecting the change in the type, number, and position of the dynamic objects on the road.
For each frame of data, identifying a straight line which each static reflection point passes through according to the position distribution condition of each static reflection point. Specifically, a hough transform method may be used.
When the straight lines corresponding to the static reflecting points are identified, the requirement on the required dynamic storage space in the implementation process is high due to the fact that the number of the static reflecting points is large and data of a plurality of periods need to be counted. In response to this problem, the dependence on storage space is reduced in a statistical manner for migration to less-powerful platforms. Data collected by the target radar is generally data in a cartesian coordinate system, and the cartesian coordinate system needs to be converted into a polar coordinate system, which requires a large amount of trigonometric function calculation, and slows down the operation speed of the system. Based on the difficulty, a table look-up mode is adopted, and the corresponding relation between the angle and the trigonometric function value under the polar coordinate system is stored in advance. For example, 30 ° corresponds to sin30 ° =0.5 and cos30 ° = 0.86. Specifically, a plurality of θ are configured within a maximum allowable offset angle range at a set granularity (e.g., 0.1 degree), for example, within a range of-10 ° to 10 °, with an interval of 0.1 ° configuration 201 degrees θ. Static reflection point (x)1,y1) And each theta is respectively substituted into a conversion formula (1) from a Cartesian coordinate system to a polar coordinate system, and r is calculated in a table look-up mode, so that a point (x) passing through the static reflection is obtained1,y1) The pair of (θ, r) points of (a). Similarly, for each static reflection point, a pair of (theta, r) points is calculated, where r is<All theta are counted within a range (e.g. 15 m) of the allowed offset distance, and a suitable angle value theta, i.e. the angle of the straight line with respect to the normal of the radar, is found. R in equation (1) is the distance of the straight line from the origin of the cartesian coordinate system.
r=xcosθ+ysinθ（1）
Fig. 3 is a schematic diagram of a radar offset angle in a cartesian coordinate system according to an embodiment of the present invention. The point O is the origin of coordinates of the radar, the axis y is the normal direction of the radar, and the axis x is the horizontal axis direction of the static reflection point of the radar, wherein the dotted line part is the parallel line of the normal of the radar. Assuming that the maximum deflection of the radar is allowed to be θ, the lines 1, 2, 3 and 4 are the lines of the largest angle possible, where the black dots represent the static reflection points detected by the radar. Substituting the coordinates of the static reflection points into the formula (1), and carrying out statistical calculation by using a Hough transform method to count each specific (theta, r) point pair, namely a straight line through which each static reflection point passes. The final offset angle θ then needs to be solved statistically.
In the embodiment, the calculation of the trigonometric function is converted into the calculation mode of multiplication and addition through table lookup, so that a large amount of time is saved, and the scheme finishes the self-calibration function of the radar by using a small amount of time and space.
After a plurality of straight lines through which each static reflection point passes are identified and obtained, effective straight lines are screened from the straight lines to participate in the subsequent statistical process. Optionally, the number of (θ, r) point pairs to which each static reflection point is mapped is counted, if the number of a certain (θ, r) point pair exceeds a threshold (e.g. 4). The corresponding straight line of the (theta, r) point pair is determined as an effective straight line and is used as the straight line corresponding to each static reflecting point in the step, so that the selected straight line can reflect the position of the real static object on the road as much as possible.
If the offset angle of the radar is not large and static objects can be detected on both sides of the road, multiple straight lines may be recognized in one frame of data, that is, multiple straight lines are recognized on the left side of the detection visual field and multiple straight lines are recognized on the right side of the detection visual field.
S130, calculating the included angle between each straight line and the normal line of the radar and the probability density of the included angle of each straight line.
Due to the complex working conditions of the road, regular reflective targets such as guardrails and the like do not always exist. And although the road condition is good, the distribution of the road reflection target is not very regular, and the distribution is stray, which may cause that the calculated value has larger deviation. For this case, a statistically derived result is needed to approach the true value (i.e., the true offset angle).
Radar normal referring to fig. 3, the angle between the straight line and the radar normal is the offset angle relative to the radar normal. Static objects are basically distributed along the road contour, and vehicles can run along the road contour, so that static reflection points acquired by the radar when no bias exists are parallel to a normal line; therefore, the angle between the straight line and the normal of the radar is consistent with the offset angle of the radar.
Under the condition that the offset angle of the radar is not changed, the more straight lines are acquired, the closer the included angle between the straight lines and the normal line is to the offset angle of the radar. In the embodiment, the probability density of each included angle is calculated, so that a straight line included angle corresponding to a larger probability density is selected, and the offset angle of the radar is determined.
Optionally, dividing the set angle range into a plurality of intervals according to the set granularity; calculating the number of times that the included angle falls in each interval; and calculating the probability density of the offset angle according to the times.
Specifically, according to the distribution position of a static object on a road and the detection angle of a radar, the set angle range is determined to be theta = -10 degrees-0 degrees, or 0 degrees-10 degrees, or-170 degrees-180 degrees, or 170 degrees-180 degrees, and the set granularity can be 0.1 degrees. The distance (r) between the straight line and the radar is limited within 15m, so that the interference of a distant object is avoided. According to the description, the included angle theta between the effective straight line in each frame of data and the normal line of the radar is calculated, 1 is added to the angle frequency corresponding to the straight line, and the frequency of each theta is counted after multiple frames to obtain a probability density curve.
S140, selecting an included angle of a straight line with the probability density meeting the requirement as a bias angle of the target radar.
Fig. 4 is a schematic diagram of a probability density curve provided by an embodiment of the invention. The method embodies the intervals in which most included angles of straight lines fall, and the probability density is higher, and the probability that the included angles of the straight lines are offset angles is higher. Because misjudgment is difficult to avoid in the detection process, a peak appears in the probability density curve, and in order to filter out the situation, the most appropriate included angle is selected by adopting a sliding window method.
Specifically, a first sliding window and a second sliding window are configured, and the size of the first sliding window (for example, 2 °) is larger than that of the second sliding window (for example, 0.8 °). Sliding the first sliding window on a probability density curve of an included angle, and selecting a first angle range with the largest window coverage area; as shown in fig. 4. Sliding the second sliding window on the probability density curve of the first angle range, and selecting a second angle range with the largest window coverage area; and determining the offset angle of the target radar according to the second angle range. Optionally, the second angle range is directly used as a bias angle range of the radar, for example, the bias angle range is-2.1 to-2.5 degrees; alternatively, the angle corresponding to the highest probability density is taken as the offset angle in the second angle range.
S150, self-calibrating the target radar according to the offset angle.
The millimeter wave radar in the embodiment has a self-calibration function, and compensates the detected data according to the offset angle, so that real data is output.
Optionally, the offset angle is uploaded to a cloud platform, so that the cloud platform can determine whether the offset angle meets an adjustment condition; if the adjustment condition is met, issuing an adjustment instruction to the vehicle; responding to the adjusting instruction, and performing software self-calibration on the target radar according to the offset angle.
The adjustment condition includes that the vehicle is in an early warning state, the offset angle is larger than a set value (such as 3 degrees), and the target radar needs to be calibrated at the moment, so that unnecessary operation is avoided.
The method does not depend on any fixed reference object, the linear equation of the static object on the road profile is solved according to the distribution characteristics of the static object on the road profile, the probability density of the included angle is further calculated, and the bias angle of the radar is determined by adopting the idea of big data statistics. The calibration method is simpler and shorter in time consumption, and is suitable for almost all road scenes.
In an actual driving scene, the driving behavior of a driver may be random, the driver does not necessarily go straight along a road, behaviors such as turning, lane changing and overtaking exist, and the calibration result is seriously interfered under the working condition. For this difficulty, the acquisition of the position of the static reflection point should satisfy a certain condition by the vehicle. Specifically, the determining the position of the static reflection point from each frame of the multi-frame data comprises: acquiring the speed and the yaw rate of the vehicle during each frame of data acquisition; and if the vehicle speed is above the set vehicle speed threshold value and the yaw rate is within the set angular speed range, determining the position of the static reflection point from the frame data.
Through a large number of tests, when the vehicle speed is more than 15km/h and the amplitude of the yaw velocity is less than 0.5 degrees/s after filtering, the straight line determined according to the static reflection point can truly reflect the road profile.
Fig. 5 is a schematic diagram of a display effect before calibration according to an embodiment of the present invention, where the left side of fig. 5 is a real scene shot by a camera, and the right side of fig. 5 is an acquired static reflection point, where the calculated radar offset angle is 9.55 °. The position of the static reflection point can be changed along with the running of the vehicle, and if the collected points are enough, the radar offset angle obtained through statistics can be gradually converged. Fig. 6 is a schematic diagram of a calibrated display effect provided by an embodiment of the present invention, where the left side of fig. 6 is a real scene, and the right side is a static reflection point after calibration and compensation.
Fig. 7 is a schematic structural diagram of a reference-object-free self-calibration apparatus of a millimeter wave radar provided in an embodiment of the present invention, including: an acquisition module 610, an identification module 620, a calculation module 630, a selection module 640, and a calibration module 650.
The acquisition module 610 is used for acquiring multi-frame data detected by a target radar in the running process of a vehicle on an actual road, and determining the position of a static reflection point from each frame of data of the multi-frame data;
the identifying module 620 is configured to identify a straight line corresponding to each static reflection point according to a position of each static reflection point in each frame of data;
a calculating module 630, configured to calculate an offset angle of each line with respect to a radar normal, and a probability density of the offset angle of each line;
a selecting module 640, configured to select a bias angle of a straight line with a probability density meeting a requirement as a bias angle of the target radar;
and the calibration module 650 is configured to perform self-calibration on the target radar according to the offset angle.
Optionally, the selecting module 640 includes: a construction unit for constructing a first sliding window and a second sliding window, the first sliding window being larger in size than the second sliding window; the first sliding unit is used for sliding the first sliding window on a probability density curve of an included angle and selecting a first angle range with the largest window coverage area; the second sliding unit is used for sliding the second sliding window on the probability density curve of the first angle range and selecting a second angle range with the largest window coverage area; and the determining unit is used for determining the offset angle of the target radar according to the second angle range.
Optionally, when the calculating module 630 calculates the probability density of the included angle of each straight line, it is specifically configured to: dividing the set angle range into a plurality of intervals according to the set granularity; calculating the number of times that the included angle falls in each interval; and calculating the probability density of the included angle according to the times.
Optionally, when the acquisition module 610 determines the position of the static reflection point from each frame of the multi-frame data, it is specifically configured to: acquiring the speed and the yaw rate of the vehicle during each frame of data acquisition; and if the vehicle speed is above the set vehicle speed threshold value and the yaw rate is within the set angular speed range, determining the position of the static reflection point from the frame data.
Optionally, the calibration module 650 is specifically configured to upload the offset angle to a cloud platform, so that the cloud platform determines whether the offset angle meets an adjustment condition; if the adjustment condition is met, issuing an adjustment instruction to the vehicle; responding to the adjusting instruction, and performing software self-calibration on the target radar according to the offset angle.
Optionally, the identifying module 620 is specifically configured to determine a point coordinate of the position of each static reflection point in each frame of data in a cartesian coordinate system; mapping point coordinates under a Cartesian coordinate system to a polar coordinate system by adopting a table look-up mode according to a conversion formula from the Cartesian coordinate system to the polar coordinate system to obtain an angle of a straight line under the polar coordinate system as an included angle relative to a radar normal; the table stores the corresponding relation between the angle and the trigonometric function value under a polar coordinate system.
The reference-object-free self-calibration device for the millimeter wave radar provided by the embodiment of the invention can execute the method provided by any embodiment, and has corresponding technical effects.
Fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, as shown in fig. 8, the electronic device includes a processor 70, a memory 71, an input device 72, and an output device 73; the number of the processors 70 in the electronic device may be one or more, and one processor 70 is taken as an example in fig. 8; the processor 70, the memory 71, the input device 72 and the output device 73 in the electronic apparatus may be connected by a bus or other means, and the bus connection is exemplified in fig. 8.
The memory 71 is a computer-readable storage medium, and can be used for storing software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the method for reference-free self-calibration of millimeter-wave radar in the embodiment of the present invention (for example, the acquisition module 610, the identification module 620, the calculation module 630, the selection module 640, and the calibration module 650 in the reference-free self-calibration apparatus of millimeter-wave radar). The processor 70 executes various functional applications and data processing of the electronic device by running software programs, instructions and modules stored in the memory 71, that is, the above-mentioned reference-free self-calibration method for the millimeter wave radar is realized.
The memory 71 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the memory 71 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, the memory 71 may further include memory located remotely from the processor 70, which may be connected to the electronic device through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 72 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function controls of the electronic apparatus. The output device 73 may include display electronics such as a display screen.
The embodiment of the invention also provides a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the method for the reference-free self-calibration of the millimeter wave radar in any embodiment is realized.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, or the like, as well as conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or electronic device. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions deviate from the technical solutions of the embodiments of the present invention.
Claims (10)
1. A reference-free self-calibration method for a millimeter wave radar is characterized by comprising the following steps:
the method comprises the steps that in the running process of a vehicle on an actual road, multi-frame data detected by a target radar are collected, and the position of a static reflection point is determined from each frame of data of the multi-frame data;
identifying a straight line corresponding to each static reflecting point according to the position of each static reflecting point in each frame of data;
calculating the included angle between each straight line and the normal line of the radar and the probability density of the included angle of each straight line;
selecting an included angle of a straight line with probability density meeting requirements as a bias angle of the target radar by adopting a sliding window method;
and self-calibrating the target radar according to the offset angle.
2. The method of claim 1, wherein calculating the probability density of the included angle of each line comprises:
dividing the set angle range into a plurality of intervals according to the set granularity;
calculating the number of times that the included angle falls in each interval;
and calculating the probability density of the included angle according to the times.
3. The method according to claim 1, wherein the selecting an included angle of a straight line with a probability density meeting requirements as a bias angle of the target radar comprises:
constructing a first sliding window and a second sliding window, wherein the size of the first sliding window is larger than that of the second sliding window;
sliding the first sliding window on a probability density curve of an included angle, and selecting a first angle range with the largest window coverage area;
sliding the second sliding window on the probability density curve of the first angle range, and selecting a second angle range with the largest window coverage area;
and determining the offset angle of the target radar according to the second angle range.
4. The method according to claim 1, wherein the determining the position of the static reflection point from each frame of the plurality of frames of data comprises:
acquiring the speed and the yaw rate of the vehicle during each frame of data acquisition;
and if the vehicle speed is above the set vehicle speed threshold value and the yaw rate is within the set angular speed range, determining the position of the static reflection point from the frame data.
5. The method of claim 1, wherein the self-calibrating the target radar according to the offset angle comprises:
uploading the offset angle to a cloud platform, so that the cloud platform can judge whether the offset angle meets an adjusting condition; if the adjustment condition is met, issuing an adjustment instruction to the vehicle;
responding to the adjusting instruction, and performing software self-calibration on the target radar according to the offset angle.
6. The method of claim 1, wherein identifying the straight line corresponding to each static reflection point according to the position of each static reflection point in each frame of data comprises:
determining the point coordinates of the positions of the static reflection points in each frame of data in a Cartesian coordinate system;
mapping point coordinates under a Cartesian coordinate system to a polar coordinate system by adopting a table look-up mode according to a conversion formula from the Cartesian coordinate system to the polar coordinate system to obtain an angle of a straight line under the polar coordinate system as an included angle relative to a radar normal;
the table stores the corresponding relation between the angle and the trigonometric function value under a polar coordinate system.
7. A no-reference object self-calibration device of a millimeter wave radar is characterized by comprising:
the acquisition module is used for acquiring multi-frame data detected by a target radar in the running process of a vehicle on an actual road and determining the position of a static reflection point from each frame of data of the multi-frame data;
the identification module is used for identifying straight lines corresponding to the static reflecting points according to the positions of the static reflecting points in each frame of data;
the calculation module is used for calculating the offset angle of each straight line relative to the normal line of the radar and the probability density of the offset angle of each straight line;
the selection module is used for selecting the offset angle of the straight line with the probability density meeting the requirement as the offset angle of the target radar by adopting a sliding window method;
and the calibration module is used for self-calibrating the target radar according to the offset angle.
8. The apparatus of claim 7, wherein the selection module comprises:
a construction unit for constructing a first sliding window and a second sliding window, the first sliding window being larger in size than the second sliding window;
the first sliding unit is used for sliding the first sliding window on a probability density curve of an included angle and selecting a first angle range with the largest window coverage area;
the second sliding unit is used for sliding the second sliding window on the probability density curve of the first angle range and selecting a second angle range with the largest window coverage area;
and the determining unit is used for determining the offset angle of the target radar according to the second angle range.
9. An electronic device, comprising:
one or more processors;
a memory for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method for referenceless self-calibration of millimeter wave radar as recited in any of claims 1-6.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements a method for reference-free self-calibration of a millimeter wave radar according to any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110754125.3A CN113253219B (en) | 2021-07-05 | 2021-07-05 | No-reference object self-calibration method, device, equipment and medium of millimeter wave radar |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110754125.3A CN113253219B (en) | 2021-07-05 | 2021-07-05 | No-reference object self-calibration method, device, equipment and medium of millimeter wave radar |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113253219A CN113253219A (en) | 2021-08-13 |
| CN113253219B true CN113253219B (en) | 2021-09-17 |
Family
ID=77190697
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110754125.3A Active CN113253219B (en) | 2021-07-05 | 2021-07-05 | No-reference object self-calibration method, device, equipment and medium of millimeter wave radar |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113253219B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115371719B (en) * | 2022-10-10 | 2023-01-24 | 福思(杭州)智能科技有限公司 | Parameter calibration method and device for detection equipment, storage medium and electronic device |
| CN115327501B (en) * | 2022-10-13 | 2022-12-23 | 南京隼眼电子科技有限公司 | Horizontal installation angle self-calibration method and device, electronic equipment and storage medium |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105711569B (en) * | 2016-01-29 | 2019-04-05 | 大连楼兰科技股份有限公司 | Autobrake system and method |
| CN113795773A (en) * | 2019-03-08 | 2021-12-14 | 欧司朗股份有限公司 | Component for a LIDAR sensor system, LIDAR sensor device, method for a LIDAR sensor system and method for a LIDAR sensor device |
| CN110379203B (en) * | 2019-06-21 | 2021-08-03 | 江苏大学 | Driving steering collision early warning method |
| CN111566505A (en) * | 2019-06-28 | 2020-08-21 | 深圳市大疆创新科技有限公司 | Calibration method and system for installation angle of millimeter wave radar component and movable platform |
| CN112114293A (en) * | 2019-12-29 | 2020-12-22 | 的卢技术有限公司 | Device and method for testing performance of millimeter wave radar under multipath condition |
| CN111221334B (en) * | 2020-01-17 | 2021-09-21 | 清华大学 | Environmental sensor simulation method for simulating automatic driving automobile |
| CN111369630A (en) * | 2020-02-27 | 2020-07-03 | 河海大学常州校区 | Method for calibrating multi-line laser radar and camera |
| CN111624566B (en) * | 2020-07-30 | 2021-04-16 | 北汽福田汽车股份有限公司 | Radar installation angle calibration method and device |
-
2021
- 2021-07-05 CN CN202110754125.3A patent/CN113253219B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN113253219A (en) | 2021-08-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20200348408A1 (en) | Vehicle Positioning Method and Vehicle Positioning Apparatus | |
| US11982771B2 (en) | Method for identification of a noise point used for LiDAR, and LiDAR system | |
| CN113253219B (en) | No-reference object self-calibration method, device, equipment and medium of millimeter wave radar | |
| US10488507B2 (en) | Surrounding environment estimation device and surrounding environment estimating method | |
| US10386476B2 (en) | Obstacle detection method and apparatus for vehicle-mounted radar system | |
| EP3503490A1 (en) | Environment sensing method and base station | |
| CN112213725B (en) | Multipath false alarm suppression method and device for vehicle-mounted radar and terminal equipment | |
| JP6683714B2 (en) | System and method for detection of radar vertical misalignment | |
| CN107507417B (en) | A kind of smartway partitioning method and device based on microwave radar echo-signal | |
| CN112562314A (en) | Road end sensing method and device based on deep fusion, road end equipment and system | |
| KR102440355B1 (en) | Deep Learning-based Ocean Cluster Data Measurement System Using Sea Level Wave Reflectance | |
| CN112233416A (en) | Traffic flow detection method and device | |
| CN112763993A (en) | Method and device for calibrating radar parameters, electronic equipment and storage medium | |
| KR102060286B1 (en) | Radar object detection threshold value determination method using image information and radar object information generation device using the same | |
| CN117372979A (en) | Road inspection method, device, electronic equipment and storage medium | |
| CN111090106A (en) | Atmospheric visibility measuring system, method and device | |
| WO2022198637A1 (en) | Point cloud noise filtering method and system, and movable platform | |
| CN113734176A (en) | Environment sensing system and method for intelligent driving vehicle, vehicle and storage medium | |
| CN117471485A (en) | Expressway roadbed high slope displacement monitoring method based on unmanned plane laser radar | |
| CN113050081A (en) | Method and device for detecting shelter, radar, vehicle and storage medium | |
| CN114371450A (en) | Radar anti-interference identification method and device and computer equipment | |
| CN114093174B (en) | Visibility detection method, device, terminal and computer readable storage medium | |
| CN114859337A (en) | Data processing method and device, electronic equipment and computer storage medium | |
| CN112466114A (en) | Traffic monitoring system and method based on millimeter wave technology | |
| KR20210147381A (en) | Radar Device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |